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Microsoft Data Engineering on Microsoft Azure : DP-203

DP-203

Exam Code: DP-203

Exam Name: Data Engineering on Microsoft Azure

Updated: Aug 27, 2026

Q & A: 365 Questions and Answers

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Languages: English, Chinese (Simplified), Japanese, Korean

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: design and implement data storage; design and develop data processing; design and implement data security; and monitor and optimize data storage and data processing.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-203

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What is the cost of the Microsoft DP-203 Exam

The Microsoft DP-203 Exam cost is $165 USD.

What is Microsoft DP-203 Certification

Microsoft DP-203 (Designing Data Platform Solutions on Microsoft Azure) certification is a great way to validate your hands-on experience with cloud platforms, data architecture, and database technologies. This exam is designed to determine the competency of candidates to design distributed data solutions for enterprise applications based on Azure technologies. Before you begin studying for this exam, there are a few terms that you should familiarize yourself with. First and foremost, you should understand the difference between Microsoft SQL Server, Microsoft SQL Database, and Microsoft Azure SQL Database. Exam objectives are associated with these products; therefore, it is important to know when you will be tested on each one. Microsoft DP-203 Dumps tests a candidate's knowledge of Microsoft technologies used for building a data platform and cloud environment. Microsoft DP-203 is a certification of data engineers. The certification exam is designed to test the skills of designing, deploying, and managing Microsoft HDInsight and Microsoft Azure SQL Data Warehouse clusters for business intelligence and analytics solutions.

Microsoft DP-203 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and implement data storage40–45%- Design data storage structures
  • 1. Recommend storage solutions for analytical workloads
    • 2. Design for scalability and performance
      • 3. Design partitioning strategies
        • 4. Design for data durability and availability
          - Implement data storage
          • 1. Implement relational and non-relational data stores
            • 2. Manage data lifecycle and retention policies
              • 3. Implement data lake storage
                • 4. Create and configure data storage accounts
                  Topic 2: Monitor and optimize data storage and data processing10–15%- Optimize performance and cost
                  • 1. Optimize storage and compute resources
                    • 2. Tune pipelines and workloads
                      • 3. Improve query and processing efficiency
                        - Monitor data solutions
                        • 1. Monitor pipeline execution and errors
                          • 2. Monitor storage performance and health
                            • 3. Log and analyze activity and usage
                              Topic 3: Design and implement data security10–15%- Implement authentication and authorization
                              • 1. Configure identity and access management
                                • 2. Manage access to data resources
                                  - Protect data at rest and in transit
                                  • 1. Manage data privacy and compliance
                                    • 2. Configure data masking and redaction
                                      • 3. Implement encryption
                                        Topic 4: Design and develop data processing25–30%- Design data processing pipelines
                                        • 1. Design orchestration and scheduling
                                          • 2. Design for data integration and transformation
                                            • 3. Design batch processing solutions
                                              • 4. Design real-time processing solutions
                                                - Develop data processing solutions
                                                • 1. Transform data using Spark, SQL, or other tools
                                                  • 2. Implement incremental processing
                                                    • 3. Implement data ingestion
                                                      • 4. Manage data flows and dependencies
                                                        DP-203 Related Exams
                                                        DP-203J - Data Engineering on Microsoft Azure (DP-203日本語版)
                                                        DP-203-KR - Data Engineering on Microsoft Azure (DP-203 Korean Version)
                                                        DP-203-Deutsch - Data Engineering on Microsoft Azure (DP-203 Deutsch Version)
                                                        Related Certifications
                                                        Microsoft Certified: Identity and Access Administrator Associate
                                                        Dynamics-POS-2009
                                                        Microsoft Azure SQL Data Warehous
                                                        Microsoft Certified: Data Analyst Associate
                                                        Microsoft Project
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